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ABSTRACT
Diabetes mellitus type 2 has become one of the major causes of premature diseases and death in many countries. It accounts for the majority of diabetes cases around the world. Thus, we need to develop a system that diagnoses type 2 diabetes. In this project, a fuzzy expert system is proposed using the Mamdani fuzzy inference system to diagnose type 2 diabetes effectively. The data set were fuzzified into variables that were used to develop rule. The fuzzy inference system followed three transformation stages; fuzzification, rule based and defuzzification processes. The fuzzy expert system is built using the Mamdani fuzzy inference system in Matlab. Implementing this system involves four main steps which are fuzzification, rules evaluation, outputs aggregation, and defuzzification. The fuzzy expert system achieved a prediction accuracy of 92.5%, with a specificity of 94%, a sensitivity of 90%, a precision of 89%, and an F-measure of 90%.
